There mainly exist three categories of existing LP models: heuristic feature based [1]}, [2]}, [3]}, [4]}, [5]}, latent embedding based [6]}, [7]}, [8]}, [9]}, [10]}, [11]}, and neural network based ones.
The neural network-based link prediction models, which use neural layers to explore non-linear deep structural feature, have been primarily investigated in recent years.
Variational graph auto-encoders [12]} predict links by encoding graph with graph convolutional layer [13]}.
Two cutting-edge neural network based LP models WLNM [14]} and SEAL [15]} transfer the union neighborhood of a pair of nodes as a meaningful matrix and encode the graph structural features with DGCNN [16]}.
More recently, [17]}, [18]} summarized the architectures popular LP models, and formally define the encoders and decoders as the important components in LP architectures.
